def orient(self, orientname, orientclass, paralib):
''' add section instance to the seclist.
inputs:
orientname -- user defined name of orient, use as key
orientclass -- class name of the orient, used to retrive class
paralib -- dict of orient properties to create orient
'''
orient = self.get_class(orientclass)
self.orientlist[orientname] = orient(paralib)
def orient(self,orientname,orientclass,paralib):
''' add section instance to the seclist.
inputs:
orientname -- user defined name of orient, use as key
orientclass -- class name of the orient, used to retrive class
paralib -- dict of orient properties to create orient
'''
orient = self.get_class(orientclass)
self.orientlist[orientname] = orient(paralib)
def load_stl(self, filename):
self.geometry = [] # Clear previous geometry data
self.name = [] # Clear previous STL model name
self.normal = [] # Clear previous STL normal data
fp = open(filename, 'r') # Open and read selected file into memory
# Loop over each line in the STL file
for line in fp.readlines():
parts = line.split() # Split line into parts by spaces
if len(parts) > 0:
# Start of filename, store embedded filename
if parts[0] == 'solid':
self.name = line[6:-1]
# Beginning of a new face - store normals and begin new triangle variable
if parts[0] == 'facet':
triangle = []
# Select face normal components
self.normal_face = (float(parts[2]), float(parts[3]),
float(parts[4]), 1)
# Store all the vertex points in 'triangle'
if parts[0] == 'vertex':
triangle.append(
(float(parts[1]), float(parts[2]), float(parts[3]), 1))
# End of face - append new face to the model data
if parts[0] == 'endloop':
self.geometry.append(
[triangle[0], triangle[1], triangle[2]])
self.normal.append(self.normal_face)
fp.close()
# Convert lists to numpy arrays of the correct dimensions (Nx4 matrices)
self.normal = np.asarray(self.normal).reshape((-1, 4))
self.geometry = np.asarray(self.geometry).reshape((-1, 4))
self.geometry = orient(
self.geometry, embed_w,
embed_h) # Orient object geometry in screen space
window.title("STL Viewer Application - " +
self.name) # Put filename in the GUI header
model2_file='*D021KM*{0:s}*hdf'.format(granule_info)
model2_file=glob.glob(model2_file)[0]
sdrad=pyhdf.SD.SD(model2_file)
longWave=sdrad.select('EV_1KM_Emissive')
allRadiances=longWave.get()
model35_file='*D35*{0:s}*hdf'.format(granule_info)
model35_file=glob.glob(model35_file)[0]
mask=pyhdf.SD.SD(model35_file)
maskVals=mask.select('Cloud_Mask')
maskVals=maskVals.get()
byte0=maskVals[0,...] #get the first byte
maskout,landout=bitmap.getmask_zero(byte0)
maskout=maskout.astype(np.float32)
landout=landout.astype(np.float32)
fullLats,fullLons,maskout=orient(fullLats_raw,fullLons_raw,maskout)
fullLats,fullLons,landout=orient(fullLats_raw,fullLons_raw,landout)
#
# find the index for channel 31 (it's 10, i.e. channel 31 is
# the 11th channel)
#
theChans=longWave.attributes()['band_names']
band_names=theChans.split(',')
index31=band_names.index('31')
#
# get the radiances as 16 bit integers
#
chan31=allRadiances[index31,:,:]
#
# apply scale and offset to convert to 64 bit floats
#
# -1: No obstacle yet # 0: Obstacle seen, right after first turn to the right # 1: Walking forward along the box # 2: Last step counterForZero = 1 notches = 0 goStraight() while 1: if seenObstacle(): if ANGULAR_CHECKS: notches = orient.orient() else: notches = 0 print "notches = %d" % notches avoidingObstacle = 0 turnRight90() goStraight() if avoidingObstacle >= 0 and avoidingObstacle <= 1: sleep(TIME_BETWEEN_CHECKES) # Check the side turnLeft90() if seenObstacle(300): turnRight90() else:
#
# get the radiances as 16 bit integers
#
chan31 = allRadiances[index31, :, :]
#
# apply scale and offset to convert to 64 bit floats
#
scale31 = longWave.attributes()["radiance_scales"][index31]
offset31 = longWave.attributes()["radiance_offsets"][index31]
chan31 = scale31 * (chan31 - offset31)
#
# flip the array if necessary so col[0] is west and row[0]
# is south
#
fullLats, fullLons, chan31 = orient(fullLats, fullLons, chan31)
#
# take a small subset to speed things up
#
partLats = fullLats[:max_rows, :max_cols]
partLons = fullLons[:max_rows, :max_cols]
partChan31 = chan31[:max_rows, :max_cols]
fig0a = plt.figure(1)
fig0a.clf()
axis0a = fig0a.add_subplot(111)
im = axis0a.contourf(partLats)
cb = plt.colorbar(im)
the_label = cb.ax.set_ylabel("latitude (deg)", rotation=270)
axis0a.set_title("partial scene latitude")
#
chan1raw=allRadiances[index1,:,:]
#
# apply scale and offset to convert to 64 bit floats
#
scale1=shortWave.attributes()['radiance_scales'][index1]
offset1=shortWave.attributes()['radiance_offsets'][index1]
chan1 = scale1 * (chan1raw - offset1)
scale1ref=shortWave.attributes()['reflectance_scales'][index1]
offset1ref=shortWave.attributes()['reflectance_offsets'][index1]
chan1ref = scale1ref * (chan1raw - offset1ref)
sdrad.end()
fullLats,fullLons,chan1=orient(fullLats_raw,fullLons_raw,chan1)
fullLats,fullLons,chan1ref=orient(fullLats_raw,fullLons_raw,chan1ref)
#
# get the bounding box to set the lat/lon grid
#
north,south,east,west=meta_data['nsew']
#
# select none here to see the full image
#
max_rows= None
max_cols= None
partLats=fullLats[:max_rows,:max_cols]
partLons=fullLons[:max_rows,:max_cols]
partRads=chan1[:max_rows,:max_cols]
partRefs=chan1ref[:max_rows,:max_cols]
#
# now make sure we get the same counts in each bin
# as the numpy histogram routine
#
granule_info = "A2010215.2145.005"
model3_file = "*D03*{0:s}*hdf".format(granule_info)
model3_file = glob.glob(model3_file)[0]
my_parser = metaParse(filename=model3_file)
meta_data = my_parser.get_info()
sdgeom = pyhdf.SD.SD(model3_file)
fullLats = sdgeom.select("Latitude")
fullLats = fullLats.get()
fullLons = sdgeom.select("Longitude")
fullLons = fullLons.get()
sdgeom.end()
fullLats, fullLons, fullLats = orient(fullLats, fullLons, fullLats)
#
# get the bounding box to set the lat/lon grid
#
north, south, east, west = meta_data["nsew"]
max_rows = 200
max_cols = 200
partLats = fullLats[:max_rows, :max_cols]
partLons = fullLons[:max_rows, :max_cols]
numlatbins = 200
numlonbins = 200
tic = time.clock()
bin_lats = fastbin(south, north, numlatbins, -999, -888)
bin_lons = fastbin(west, east, numlonbins, -999, -888)
print "sending in: ", partLats.dtype, partLons.dtype
