def testFIR(self):
smooth = np.array([0.25, 0.5, 0.25])
d = np.arange(10)
filtered = fir(d, smooth, zero_edge=False)
print d, '--', smooth, '(keep edge) -->', filtered
self.assertTrue(np.all( filtered == d))
filtered = fir(d, smooth, zero_edge=True)
print d, '--', smooth, '-->', filtered
self.assertEquals(0, filtered[9])
d = np.zeros(10)
d[5] = 10
filtered = fir(d, smooth)
print d, '--', smooth, '-->', filtered
self.assertEquals(5.0, filtered[5])
d = np.zeros(10)
d[5:10] = np.ones(5)
filtered = fir(d, smooth)
print d, '--', smooth, '-->', filtered
self.assertEquals(0.0, filtered[3])
self.assertEquals(0.25, filtered[4])
self.assertEquals(0.75, filtered[5])
self.assertEquals(1.0, filtered[6])
diff = np.array([-0.5, 0, 0.5])
filtered = fir(d, diff)
print d, '--', diff, '-->', filtered
def makeshapes(x, y, type=None, z=None, m=None):
"""
Make shapes by x and y coordinates.
:param x: (*array_like*) X coordinates.
:param y: (*array_like*) Y coordinates.
:param type: (*string*) Shape type [point | line | polygon].
:param z: (*array_like*) Z coordinates.
:param m: (*array_like*) M coordinates.
:returns: Shapes
"""
shapes = []
if isinstance(x, (int, float)):
shape = PointShape()
shape.setPoint(PointD(x, y))
shapes.append(shape)
else:
x = np.asarray(x).array
y = np.asarray(y).array
if not z is None:
if m is None:
m = np.zeros(len(z)).array
else:
m = np.asarray(m).array
z = np.asarray(z).array
if type == 'point':
if z is None:
shapes = ShapeUtil.createPointShapes(x, y)
else:
shapes = ShapeUtil.createPointShapes(x, y, z, m)
elif type == 'line':
if z is None:
shapes = ShapeUtil.createPolylineShapes(x, y)
else:
shapes = ShapeUtil.createPolylineShapes(x, y, z, m)
elif type == 'polygon':
if z is None:
shapes = ShapeUtil.createPolygonShapes(x, y)
else:
shapes = ShapeUtil.createPolygonShape(x, y, z, m)
return shapes
def fir(data, fir, zero_edge=True):
"""FIR filter
@param data: Array data
@param fir: FIR filter elements
@param zero_edge: Set edge elements in result to 0, or preserve original data?
@return: Filtered array
"""
L = len(fir)
N = len(data)
mid = int(len(fir)/2)
if zero_edge:
result = np.zeros(N)
else:
result = np.array(data)
for i in range(mid, N-mid):
# index into 'data' at left edge of filter
i0 = i-mid
# print fir, data[i0:(i0+L)], fir * data[i0:(i0+L)], sum(fir * data[i0:(i0+L)])
result[i] = sum(fir * data[i0:(i0+L)])
return result