Use astype for casting numpy data

In [2]: numpy.array([[0, -128], [-100, 100], [37, -80], [255, 0]], numpy.int8)
   ...:
<ipython-input-2-a2ef1427d77a>:1: DeprecationWarning: NumPy will stop allowing conversion of out-of-bound Python integers to integer arrays.  The conversion of 255 to int8 will fail in the future.
For the old behavior, usually:
    np.array(value).astype(dtype)
will give the desired result (the cast overflows).

forestatrisk/project/deforest.py

@@ -168,7 +168,7 @@ def deforest(input_raster, hectares, output_file="output/fcc.tif", blk_rows=128)
         # Number of pixels that are really deforested
         deforpix = np.nonzero(prob_data >= threshold)
         # Forest-cover change
-        for_data = np.ones(shape=prob_data.shape).astype(np.int8)
+        for_data = np.ones(shape=prob_data.shape).astype(int)
         for_data = for_data * 255  # nodata
         for_data[prob_data != 0] = 1
         for_data[deforpix] = 0