def whittle(cloud, polygons):
"""
Parameters
----------
cloud : ndarray
Mx3 array containing the point cloud. Columns are x, y, and z
Should be centered about the origin
polygons : list of ndarray
Each array is Mx2 and represents a series of x, y points defining a
polygon.
Returns
-------
cloud : ndarray
Mx3 array representing the points from the original cloud that are
contained inside the 3d volume defined by the series of polygons
"""
# Divide half the circle evenly among the polygons
angle = np.pi / len(polygons)
rotation_matrix = get_rotation_matrix(angle)
for polygon in polygons:
# Find and remove the points that fall outside the current projection
mask = mlab.inside_poly(cloud[:, 1:], polygon)
cloud = cloud[mask]
1/0
# Rotate the cloud and go to the next projection
cloud = cloud.dot(rotation_matrix)
return cloud
def whittle(cloud, polygons):
"""
Parameters
----------
cloud : ndarray
Mx3 array containing the point cloud. Columns are x, y, and z
Should be centered about the origin
polygons : list of ndarray
Each array is Mx2 and represents a series of x, y points defining a
polygon.
Returns
-------
cloud : ndarray
Mx3 array representing the points from the original cloud that are
contained inside the 3d volume defined by the series of polygons
"""
# Divide half the circle evenly among the polygons
angle = np.pi / len(polygons)
rotation_matrix = get_rotation_matrix(angle)
for polygon in polygons:
# Find and remove the points that fall outside the current projection
mask = mlab.inside_poly(cloud[:, 1:], polygon)
cloud = cloud[mask]
1/0
# Rotate the cloud and go to the next projection
cloud = cloud.dot(rotation_matrix)
return cloud
def polygon_average(self, pvert, bluered='blue'):
"""Averages within a polygon"""
self.show_lines([
numpy.array(pvert[0]).T,
],
edgecolor=bluered,
linewidth=2)
avgfigure = mpl.figure()
avgax = avgfigure.add_subplot(111)
for i, hdu in enumerate(self.extra_hdus):
points = self._get_points(hdu)
vel = getaxes(hdu.header, 1)
#mask = points_inside_poly(points, pvert[0])
mask = inside_poly(points, pvert[0])
navg = len(numpy.where(mask)[0])
hdunew = hdu.data.copy()
ny, nx, nv = hdunew.shape
hdunew = hdunew.reshape((ny * nx), nv)
poly_avg = hdunew[mask, :].mean(axis=0)
avgax.plot(vel,
poly_avg,
linestyle='steps-mid',
label='%s %s polygon' %
(self._get_hdu_title(i), bluered))
avgax.set_title("Average made from %s qualifying points" % navg)
avgax.legend(loc='best')
avgfigure.canvas.draw()
self.refresh()
def getdataInRect(self):
# Get the data from the Graphicsitem
self.getDataItem()
x = self.dataxy[0]
y = self.dataxy[1]
# Rect Edges
Xbl = (self.Coords[0], self.Coords[1]) # bottom left
Xbr = (self.Coords[2], self.Coords[1]) # bottom right
Xtr = (self.Coords[2], self.Coords[3]) # top right
Xtl = (self.Coords[0], self.Coords[3]) # top left
#Make a list of [(x0,y0),(x1,y1) ...]
self.xy = list()
for i in x:
tmp = (x[i], y[i])
self.xy.append(tmp)
# exemple = inside_poly([(x0,y0),(x1,y1),...],[Xbl, Xbr, Xtr, Xtl])
self.insideIndex = inside_poly(self.xy, [Xbl, Xbr, Xtr, Xtl])
def getIntensity(self, lat, long):
# TODO: Test
long += 5.0
lat += 10.0
wind_kt = 0.0 # wind speed in knots
for i in xrange(self.data.numRecords):
if len(inside_poly([[long, lat]], self.data.shape(i).points)) > 0:
# Find the wind corresponding to the bus latutude and longitude
wind_kt = max(wind_kt, float(self.data.record(i)[1]))
# Converting from knott to mph (1 kt = 1.15077945 miles per hour)
wind_mph = wind_kt * 1.15077945
# Converting from mph wind to mph gust (1 mph wind = 1.3 mph gust)
gust_mph = wind_mph * 1.3
return gust_mph
def getdataInRect(self):
# Get the data from the Graphicsitem
self.getDataItem()
x = self.dataxy[0]
y = self.dataxy[1]
# Rect Edges
Xbl = (self.Coords[0], self.Coords[1]) # bottom left
Xbr = (self.Coords[2], self.Coords[1]) # bottom right
Xtr = (self.Coords[2], self.Coords[3]) # top right
Xtl = (self.Coords[0], self.Coords[3]) # top left
#Make a list of [(x0,y0),(x1,y1) ...]
self.xy = list()
for i in range(len(x)):
tmp = (x[i], y[i])
self.xy.append(tmp)
# matplotlib inside_poly function gets
# datapoints that are within polygon
self.insideIndex = inside_poly(self.xy, [Xbl, Xbr, Xtr, Xtl])
def checkPointsInPolygon(polygon_list, points_list):
inside = mlab.inside_poly(points_list, polygon_list);
return inside;
def checkPointsInPolygon(polygon_list, points_list):
inside = mlab.inside_poly(points_list, polygon_list)
return inside