adding raster stats and fminimum methods

fauxgeo/raster.py

@@ -289,18 +289,35 @@ def minimum(self, raster):
             # Implement broadcast operation
             def min_closure(nodata):
                 def mini(x):
-                    def f(x): return np.where((np.less(x, raster)), x, raster)
+                    def f(x): return np.where((np.minimum(x, raster)), x, raster)
                     return np.where((np.not_equal(x, nodata)), f(x), nodata)
                 return mini
             return self.local_op(raster, min_closure, broadcast=True)
         else:
             def min_closure(nodata):
                 def mini(x, y):
-                    def f(x, y): return np.where((np.less(x, y)), x, y)
+                    def f(x, y): return np.where((np.minimum(x, y)), x, y)
                     return np.where((np.not_equal(x, nodata)) & (np.not_equal(y, nodata)), f(x, y), nodata)
                 return mini
             return self.local_op(raster, min_closure)
 
+    def fminimum(self, raster):
+        if type(raster) in [float, int]:
+            # Implement broadcast operation
+            def min_closure(nodata):
+                def mini(x):
+                    def f(x): return np.where((np.fmin(x, raster)), x, raster)
+                    return np.where((np.not_equal(x, nodata)), f(x), nodata)
+                return mini
+            return self.local_op(raster, min_closure, broadcast=True)
+        else:
+            def min_closure(nodata):
+                def mini(x, y):
+                    def f(x, y): return np.where((np.fmin(x, y)), x, y)
+                    return np.where((np.not_equal(x, nodata)) | (np.not_equal(y, nodata)), f(x, y), nodata)
+                return mini
+            return self.local_op(raster, min_closure)
+
     def __getitem__(self):
         pass  # return numpy slice?  Raster object with sliced numpy array?
 
@@ -338,14 +355,38 @@ def get_grayscale_image(self):
     def get_heatmap_image(self):
         raise NotImplementedError
 
+    def sum(self):
+        # pygeo.calculate_raster_stats_uri(self.uri)
+        # mini, maxi, mean, stddev = pygeo.get_statistics_from_uri(self.uri)
+        raise NotImplementedError
+
+    def min(self):
+        pygeo.calculate_raster_stats_uri(self.uri)
+        mini, _, _, _ = pygeo.get_statistics_from_uri(self.uri)
+        return mini
+
+    def max(self):
+        pygeo.calculate_raster_stats_uri(self.uri)
+        _, maxi, _, _ = pygeo.get_statistics_from_uri(self.uri)
+        return maxi
+
+    def mean(self):
+        pygeo.calculate_raster_stats_uri(self.uri)
+        _, _, mean, _ = pygeo.get_statistics_from_uri(self.uri)
+        return mean
+
+    def std(self):
+        pygeo.calculate_raster_stats_uri(self.uri)
+        _, _, _, std = pygeo.get_statistics_from_uri(self.uri)
+        return std
+
     def ones(self):
         def ones_closure(nodata):
             def ones(x):
                 return np.where(x == x, 1, nodata)
             return ones
         return self.local_op(0, ones_closure, broadcast=True)
 
-
     def zeros(self):
         def zeros_closure(nodata):
             def zeros(x):

tests/test_raster.py

@@ -369,5 +369,63 @@ def test_set_nodata(self):
         assert(new_raster.get_nodata(1) == 100)
         assert(new_raster.get_band(1).data[0, 0] == 100)
 
+
+class TestRasterStats(unittest.TestCase):
+    def setUp(self):
+        self.shape = (4, 4)
+        self.array = np.ones(self.shape)
+        self.affine = Affine(1, 0, 0, 0, -1, 4)
+        self.proj = 4326
+        self.datatype = gdal.GDT_Float64
+        self.nodata_val = -9999
+        self.factory = RasterFactory(
+            self.proj, self.datatype, self.nodata_val, *self.shape, affine=self.affine)
+
+    def test_min(self):
+        raster = self.factory.alternating(1.0, 2.0)
+        assert(raster.min() == 1.0)
+
+    def test_max(self):
+        raster = self.factory.alternating(1.0, 2.0)
+        assert(raster.max() == 2.0)
+
+    def test_mean(self):
+        raster = self.factory.alternating(1.0, 2.0)
+        assert(raster.mean() == 1.5)
+
+    def test_std(self):
+        raster = self.factory.uniform(1.0)
+        assert(raster.std() == 0.0)
+
+    def test_sum(self):
+        raster = self.factory.alternating(1.0, -9999)
+        assert(raster.sum() == 8.0)
+
+class TestRasterMinimum(unittest.TestCase):
+    def setUp(self):
+        self.shape = (4, 4)
+        self.array = np.ones(self.shape)
+        self.affine = Affine(1, 0, 0, 0, -1, 4)
+        self.proj = 4326
+        self.datatype = gdal.GDT_Float64
+        self.nodata_val = -9999
+        self.factory = RasterFactory(
+            self.proj, self.datatype, self.nodata_val, *self.shape, affine=self.affine)
+
+    def test_minimum(self):
+        raster1 = self.factory.alternating(1.0, 2.0)
+        raster2 = self.factory.alternating(2.0, -9999)
+        min_raster = raster1.minimum(raster2)
+        assert(min_raster.get_band(1).data[0, 0] == 1)
+        assert(min_raster.get_band(1).data[0, 1] == -9999)
+
+    def test_fminimum(self):
+        raster1 = self.factory.alternating(1.0, 2.0)
+        raster2 = self.factory.alternating(2.0, -9999)
+        min_raster = raster1.fminimum(raster2)
+        assert(min_raster.get_band(1).data[0, 0] == 1)
+        assert(min_raster.get_band(1).data[0, 1] == 2)
+
+
 if __name__ == '__main__':
     unittest.main()