def run(inputFolder, srid, dbName, dbPass, dbUser, dbHost, dbPort, numberProcs):
# Make connection
connectionString = utils.getConnectString(dbName, dbUser, dbPass, dbHost, dbPort)
connection = psycopg2.connect(connectionString)
cursor = connection.cursor()
# Make it absolute path
inputFolder = os.path.abspath(inputFolder)
# Create table if it does not exist
cursor.execute('CREATE TABLE ' + utils.DB_TABLE_RAW + ' (filepath text, numberpoints integer, minz double precision, maxz double precision, geom public.geometry(Geometry, %s))', [srid, ])
connection.commit()
connection.close()
# Create queues for the distributed processing
tasksQueue = multiprocessing.Queue() # The queue of tasks (inputFiles)
resultsQueue = multiprocessing.Queue() # The queue of results
inputFiles = utils.getFiles(inputFolder, recursive=True)
numFiles = len(inputFiles)
# Add tasks/inputFiles
for i in range(numFiles):
tasksQueue.put(inputFiles[i])
for i in range(numberProcs): #we add as many None jobs as numberProcs to tell them to terminate (queue is FIFO)
tasksQueue.put(None)
processes = []
# We start numberProcs users processes
for i in range(numberProcs):
processes.append(multiprocessing.Process(target=runProcess,
args=(i, tasksQueue, resultsQueue, connectionString, srid)))
processes[-1].start()
# Get all the results (actually we do not need the returned values)
for i in range(numFiles):
resultsQueue.get()
print 'Completed %d of %d (%.02f%%)' % (i+1, numFiles, 100. * float(i+1) / float(numFiles))
# wait for all users to finish their execution
for i in range(numberProcs):
processes[i].join()
# Create an index for the geometries
connection = psycopg2.connect(connectionString)
cursor = connection.cursor()
cursor.execute('CREATE INDEX ' + utils.DB_TABLE_RAW + '_geom ON ' + utils.DB_TABLE_RAW + ' USING GIST ( geom )')
connection.commit()
connection.close()
def run(srid, userMail, level, bBox, dbName, dbPass, dbUser, dbHost, dbPort, baseURL, basePath):
message = ''
statusOk = True
outputAbsPath = None
timeStamp = datetime.datetime.now().strftime("%H_%M_%S_%f")
try:
# Get the extent of the bounding boxes anc check they are float values
(minX,minY,maxX,maxY) = bBox.replace('"','').replace("'","").split(' ')
for v in (minX,minY,maxX,maxY):
float(v)
# Make connection
connectionString = utils.getConnectString(dbName, dbUser, dbPass, dbHost, dbPort)
connection = psycopg2.connect(connectionString)
cursor = connection.cursor()
cursor.execute('SELECT max(level) FROM ' + utils.DB_TABLE_POTREE)
maxLevelPotree = cursor.fetchone()[0]
# print level,maxLevelPotree
if level != '':
if int(level) <= maxLevelPotree:
dbTable = utils.DB_TABLE_POTREE
else:
dbTable = utils.DB_TABLE_RAW
print 'Specified level (' + level + ') is not available in the potree data. Using raw data'
else:
dbTable = utils.DB_TABLE_RAW
estimatedNumPoints = None
if dbTable == utils.DB_TABLE_POTREE:
cursor.execute("""SELECT
floor(sum(numberpoints * (st_area(st_intersection(geom, qgeom)) / st_area(geom))))
FROM """ + utils.DB_TABLE_RAW + """, (SELECT ST_SetSRID(ST_MakeBox2D(ST_Point(""" + minX + """, """ + minY + """),ST_Point(""" + maxX + """, """ + maxY + """)), """ + str(srid) + """) as qgeom) AS B
WHERE geom && qgeom AND st_area(geom) != 0""")
estimatedNumPoints = cursor.fetchone()[0]
connection.close()
outputFileName = '%s_%s_%s_%s_%s.laz' % (timeStamp,minX,minY,maxX,maxY)
outputAbsPath = basePath + '/' + outputFileName
if os.path.isfile(outputAbsPath):
raise Exception('The file already existed!')
else:
query = 'SELECT filepath FROM ' + dbTable + ' where ST_SetSRID(ST_MakeBox2D(ST_Point(' + minX + ', ' + minY + '),ST_Point(' + maxX + ', ' + maxY + ')), ' + str(srid) + ') && geom'
if dbTable == utils.DB_TABLE_POTREE:
query += ' AND level = ' + str(level)
inputList = outputAbsPath + '.list'
connectionStringCommandLine = utils.getConnectString(dbName, dbUser, dbPass, dbHost, dbPort, cline = True)
precommand = 'psql ' + connectionStringCommandLine + ' -t -A -c "' + query + '" > ' + inputList
print precommand
os.system(precommand)
command = 'lasmerge -lof ' + inputList + ' -inside ' + minX + ' ' + minY + ' ' + maxX + ' ' + maxY + ' -merged -o ' + outputAbsPath
print command
os.system(command)
except:
statusOk = False
message = 'There was some error in the file generation: ' + traceback.format_exc()
if outputAbsPath != None and os.path.isfile(outputAbsPath) and statusOk:
(count, _, _, _, _, _, _, _, _, _, _, _, _) = utils.getPCFileDetails(outputAbsPath)
size = utils.getFileSize(outputAbsPath)
approxStr = ''
if dbTable == utils.DB_TABLE_POTREE:
approxStr = """
Note that due to the large extent of your selected area only the """ + '%.4f' % (float(count)/float(estimatedNumPoints)) + """ %% of the points are stored.
"""
content = """Subject: Data is ready
Your selected data is ready. """ + str(count) + """ points were selected and stored in """ + outputAbsPath.replace(basePath, baseURL) + """ with a size of """ + str(size) + """ MB.
""" + approxStr + """
Please download your data asap. This data will be deleted after 24 hours.
To visualize LAZ data there are a few alternatives.
For desktop-based simple visualization you can use LAStools lasview.
For web-based visualization you can use http://plas.io/
"""
else:
content = """Subject: Data is NOT ready
Your selection could not be stored. Sorry for the inconveniences."""
content += message
mailFileAbsPath = timeStamp + '_error.mail'
mailFile = open(mailFileAbsPath, 'w')
mailFile.write(content)
mailFile.close()
os.system('sendmail ' + userMail + ' < ' + mailFileAbsPath)