mirror of
https://github.com/rasterio/rasterio.git
synced 2025-12-08 17:36:12 +00:00
116 lines
3.8 KiB
ReStructuredText
116 lines
3.8 KiB
ReStructuredText
Plotting
|
|
********
|
|
|
|
Rasterio reads raster data into numpy arrays so plotting a single band as
|
|
two dimensional data can be accomplished directly with ``pyplot``.
|
|
|
|
.. code-block:: python
|
|
|
|
|
|
>>> import rasterio
|
|
>>> from matplotlib import pyplot
|
|
>>> src = rasterio.open("tests/data/RGB.byte.tif")
|
|
>>> pyplot.imshow(src.read(1), cmap='pink')
|
|
<matplotlib.image.AxesImage object at 0x...>
|
|
>>> pyplot.show = lambda : None # prevents showing during doctests
|
|
>>> pyplot.show()
|
|
|
|
|
|
.. image:: http://farm6.staticflickr.com/5032/13938576006_b99b23271b_o_d.png
|
|
|
|
Rasterio also provides ``rasterio.plot.show`` to perform common tasks such as
|
|
displaying multi-band images as RGB and labeling the axes with proper geo-referenced extents.
|
|
|
|
The first argument to ``show`` represent the data source to be plotted. This can be one of
|
|
|
|
* A ``RasterReader`` source instance
|
|
* A single band of a source, represented by a ``(src, band_index)`` tuple
|
|
* A numpy ndarray, 2D or 3D. If the array is 3D, ensure that it is in rasterio band order.
|
|
|
|
Thus the following operations for 3-band RGB data are equivalent. Note that when passing arrays,
|
|
you can pass in a transform in order to get extent labels.
|
|
|
|
|
|
.. code-block:: python
|
|
|
|
>>> from rasterio.plot import show
|
|
>>> show(src)
|
|
<matplotlib.axes._subplots.AxesSubplot object at 0x...>
|
|
>>> show(src.read(), transform=src.transform)
|
|
<matplotlib.axes._subplots.AxesSubplot object at 0x...>
|
|
|
|
|
|
.. image:: img/rgb.jpg
|
|
|
|
and similarly for single band plots. Note that you can pass in ``cmap`` to
|
|
specify a matplotlib color ramp. Any kwargs passed to ``show`` will passed
|
|
through to the underlying pyplot functions.
|
|
|
|
.. code-block:: python
|
|
|
|
>>> show((src, 2), cmap='viridis')
|
|
<matplotlib.axes._subplots.AxesSubplot object at 0x...>
|
|
>>> show(src.read(2), transform=src.transform, cmap='viridis')
|
|
<matplotlib.axes._subplots.AxesSubplot object at 0x...>
|
|
|
|
|
|
.. image:: img/singleband.jpg
|
|
|
|
You can create a figure with multiple subplots by passing the ``show(..., ax=ax1)``
|
|
argument. Also note that this example demonstrates setting the overall figure size
|
|
and sets a title for each subplot.
|
|
|
|
|
|
.. code-block:: python
|
|
|
|
>>> fig, (axr, axg, axb) = pyplot.subplots(1,3, figsize=(21,7))
|
|
>>> show((src, 1), ax=axr, cmap='Reds', title='red channel')
|
|
<matplotlib.axes._subplots.AxesSubplot object at 0x...>
|
|
>>> show((src, 2), ax=axg, cmap='Greens', title='green channel')
|
|
<matplotlib.axes._subplots.AxesSubplot object at 0x...>
|
|
>>> show((src, 3), ax=axb, cmap='Blues', title='blue channel')
|
|
<matplotlib.axes._subplots.AxesSubplot object at 0x...>
|
|
>>> pyplot.show()
|
|
|
|
|
|
.. image:: img/subplots.jpg
|
|
|
|
For single-band rasters, there is also an option to generate contours.
|
|
|
|
.. code-block:: python
|
|
|
|
>>> fig, ax = pyplot.subplots(1, figsize=(12, 12))
|
|
>>> show((src, 1), cmap='Greys_r', interpolation='none', ax=ax)
|
|
<matplotlib.axes._subplots.AxesSubplot object at 0x...>
|
|
>>> show((src, 1), contour=True, ax=ax)
|
|
<matplotlib.axes._subplots.AxesSubplot object at 0x...>
|
|
>>> pyplot.show()
|
|
|
|
.. image:: img/contours.jpg
|
|
|
|
Rasterio also provides a ``plot.show_hist`` function for generating histograms of
|
|
single or multiband rasters:
|
|
|
|
.. code-block:: python
|
|
|
|
>>> from rasterio.plot import show_hist
|
|
>>> show_hist(
|
|
... src, bins=50, lw=0.0, stacked=False, alpha=0.3,
|
|
... histtype='stepfilled', title="Histogram")
|
|
|
|
|
|
.. image:: img/hist.jpg
|
|
|
|
The ``show_hist`` function also takes an ``ax`` argument to allow subplot configurations
|
|
|
|
.. code-block:: python
|
|
|
|
>>> fig, (axrgb, axhist) = pyplot.subplots(1, 2, figsize=(14,7))
|
|
>>> show(src, ax=axrgb)
|
|
<matplotlib.axes._subplots.AxesSubplot object at 0x...>
|
|
>>> show_hist(src, bins=50, histtype='stepfilled',
|
|
... lw=0.0, stacked=False, alpha=0.3, ax=axhist)
|
|
>>> pyplot.show()
|
|
|
|
.. image:: img/rgb_hist.jpg
|