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diff --git a/step/precip_1996.npy b/step/precip_1996.npy
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diff --git a/step/test.py b/step/test.py
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+import numpy
+from skimage import draw
+import identification
+import matplotlib.pyplot
+import visualization
+
+# load some initial precip data 
+precip_data = numpy.load('precip_1996.npy', allow_pickle=True)
+
+# set a precip threshold and narrow your region of interest
+# TODO: What are out THRESHOLD units?
+THRESHOLD = 0.6 
+trimmed_data = numpy.where(precip_data < THRESHOLD, 0, precip_data)
+
+# create a structural set 
+struct = numpy.zeros((16, 16))
+rr, cc = draw.disk((7.5, 7.5), radius=8.5)
+struct[rr, cc] = 1
+
+# identify your storms
+labeled_maps = identification.identify(trimmed_data, struct)
+
+# visualize your data
+cmap = matplotlib.pyplot .get_cmap('hsv')
+visualization.storms(labeled_maps, cmap, 'Identified Storms 1996', 1, show_save='save')
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