Plotting PRISM BIL arrays using GDAL & Matplotlib

Now that the PRISM data is being released in a BIL format, I decided I should update my old post on plotting PRISM arrays. First, I tried using ndimage.imread() and matplotlib.imread(), but neither worked with the BIL format. GDAL can handle it though.

prism_tmean_normal

import matplotlib.pyplot as plt
from osgeo import gdal

prism_path = 'PRISM_tmean_30yr_normal_4kmM2_annual_bil.bil'
prism_nodata = -9999

prism_ds = gdal.Open(prism_path)
prism_band = prism_ds.GetRasterBand(1)
prism_array = prism_band.ReadAsArray().astype(np.float32)
# prism_nodata = prism_band.GetNoDataValue()
prism_array[prism_array == prism_nodata] = np.nan
prism_ds = None

plt.imshow(prism_array, cmap='viridis')
plt.show()

I really like the new Viridis colormap!

 

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