.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "io_examples/import_export/raster_from_array.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_io_examples_import_export_raster_from_array.py: Creating a raster from array ============================ This example demonstrates the creation of a raster through :func:`~geoutils.Raster.from_array`. .. GENERATED FROM PYTHON SOURCE LINES 7-12 .. code-block:: Python import numpy as np import pyproj import rasterio as rio .. GENERATED FROM PYTHON SOURCE LINES 13-14 We create a data array as :class:`~numpy.ndarray`, a transform as :class:`affine.Affine` and a coordinate reference system (CRS) as :class:`pyproj.CRS`. .. GENERATED FROM PYTHON SOURCE LINES 14-30 .. code-block:: Python import geoutils as gu # A random 3 x 3 masked array rng = np.random.default_rng(42) arr = rng.normal(size=(5, 5)) # Introduce a NaN value arr[2, 2] = np.nan # A transform with 3 x 3 pixels in a [0-1, 0-1] bound square transform = rio.transform.from_bounds(0, 0, 1, 1, 3, 3) # A CRS, here geographic (latitude/longitude) crs = pyproj.CRS.from_epsg(4326) # Create a raster rast = gu.Raster.from_array(data=arr, transform=transform, crs=crs, nodata=255) rast .. raw:: html 
Raster(
      data=[[0.30471707975443135 -1.0399841062404955 0.7504511958064572
             0.9405647163912139 -1.9510351886538364]
            [-1.302179506862318 0.12784040316728537 -0.3162425923435822
             -0.016801157504288795 -0.85304392757358]
            [0.8793979748628286 0.7777919354289483 -- 1.1272412069680329
             0.4675093422520456]
            [-0.8592924628832382 0.36875078408249884 -0.9588826008289989
             0.8784503013072725 -0.049925910986252896]
            [-0.18486236354526056 -0.6809295444039414 1.2225413386740303
             -0.15452948206880215 -0.4283278221631072]]
      transform=| 0.33, 0.00, 0.00|
                | 0.00,-0.33, 1.00|
                | 0.00, 0.00, 1.00|
      crs=EPSG:4326
      nodata=255)


.. GENERATED FROM PYTHON SOURCE LINES 31-32 We can print info on the raster. .. GENERATED FROM PYTHON SOURCE LINES 32-34 .. code-block:: Python rast.info() .. rst-class:: sphx-glr-script-out .. code-block:: none Driver: None Opened from file: None Filename: None Loaded? True Modified since load? True Grid size: 5, 5 Number of bands: 1 Data types: float64 Coordinate system: ['EPSG:4326'] Nodata value: 255 Pixel interpretation: None Pixel size: 0.3333333333333333, 0.3333333333333333 Upper left corner: 0.0, 1.0 Lower right corner: 1.6666666666666665, -0.6666666666666665 .. GENERATED FROM PYTHON SOURCE LINES 35-36 The array has been automatically cast into a :class:`~numpy.ma.MaskedArray`, to respect :class:`~geoutils.Raster.nodata` values. .. GENERATED FROM PYTHON SOURCE LINES 36-38 .. code-block:: Python rast.data .. rst-class:: sphx-glr-script-out .. code-block:: none masked_array( data=[[0.30471707975443135, -1.0399841062404955, 0.7504511958064572, 0.9405647163912139, -1.9510351886538364], [-1.302179506862318, 0.12784040316728537, -0.3162425923435822, -0.016801157504288795, -0.85304392757358], [0.8793979748628286, 0.7777919354289483, --, 1.1272412069680329, 0.4675093422520456], [-0.8592924628832382, 0.36875078408249884, -0.9588826008289989, 0.8784503013072725, -0.049925910986252896], [-0.18486236354526056, -0.6809295444039414, 1.2225413386740303, -0.15452948206880215, -0.4283278221631072]], mask=[[False, False, False, False, False], [False, False, False, False, False], [False, False, True, False, False], [False, False, False, False, False], [False, False, False, False, False]], fill_value=255.0) .. GENERATED FROM PYTHON SOURCE LINES 39-40 We could also have created directly from a :class:`~numpy.ma.MaskedArray`. .. GENERATED FROM PYTHON SOURCE LINES 40-49 .. code-block:: Python # A random mask, that will mask one out of two values on average mask = rng.integers(0, 2, size=(5, 5), dtype="bool") ma = np.ma.masked_array(data=arr, mask=mask) # This time, we pass directly the masked array rast = gu.Raster.from_array(data=ma, transform=transform, crs=crs, nodata=255) rast .. raw:: html 
Raster(
      data=[[0.30471707975443135 -1.0399841062404955 0.7504511958064572
             0.9405647163912139 --]
            [-1.302179506862318 0.12784040316728537 -0.3162425923435822 --
             -0.85304392757358]
            [-- 0.7777919354289483 -- 1.1272412069680329 --]
            [-- 0.36875078408249884 -0.9588826008289989 0.8784503013072725 --]
            [-0.18486236354526056 -0.6809295444039414 1.2225413386740303 --
             -0.4283278221631072]]
      transform=| 0.33, 0.00, 0.00|
                | 0.00,-0.33, 1.00|
                | 0.00, 0.00, 1.00|
      crs=EPSG:4326
      nodata=255)


.. GENERATED FROM PYTHON SOURCE LINES 50-52 The different functionalities of GeoUtils will respect :class:`~geoutils.Raster.nodata` values, starting with :func:`~geoutils.Raster.plot`, which will ignore them during plotting (transparent). .. GENERATED FROM PYTHON SOURCE LINES 52-53 .. code-block:: Python rast.plot(cmap="copper") .. image-sg:: /io_examples/import_export/images/sphx_glr_raster_from_array_001.png :alt: raster from array :srcset: /io_examples/import_export/images/sphx_glr_raster_from_array_001.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 0.406 seconds) .. _sphx_glr_download_io_examples_import_export_raster_from_array.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: raster_from_array.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: raster_from_array.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: raster_from_array.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_